Wijsman E M
Am J Hum Genet. 1987 Sep;41(3):356-73.
Derivation of haplotypes from pedigree data by means of likelihood techniques requires large computational resources and is thus highly limited in terms of the complexity of problems that can be analyzed. The present paper presents 20 rules of logic that are both necessary and sufficient for deriving haplotypes by means of nonstatistical techniques. As a result, automated haplotype analysis that uses these rules is fast and efficient, requiring computer memory that increases only linearly (rather than exponentially) with family size and the number of factors under analysis. Some error analysis is also possible. The rules are completely general with regard to any system of completely linked, discrete genetic markers that are autosomally inherited. There are no limitations on pedigree structure or the amount of missing data, although the existence of incomplete data usually reduces the fraction of haplotypes that can be completely determined.
通过似然技术从系谱数据推导单倍型需要大量计算资源,因此在可分析问题的复杂性方面受到极大限制。本文提出了20条逻辑规则,这些规则对于通过非统计技术推导单倍型而言既是必要的也是充分的。结果,使用这些规则的自动化单倍型分析快速且高效,所需计算机内存仅随家族大小和所分析因素的数量呈线性增加(而非指数增加)。还可以进行一些误差分析。这些规则对于任何常染色体遗传的完全连锁、离散遗传标记系统而言都是完全通用的。系谱结构或缺失数据量没有限制,尽管不完全数据的存在通常会降低能够完全确定的单倍型比例。